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Investigación en Educación Médica

2024, Number 50

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Inv Ed Med 2024; 13 (50)

Mental load in low fidelity simulation associated with interactive instructional material

Herrera-Aliaga E, Moreno GX, Orellana-Walden R, Madrid AG, Ruiz AC

Language: Spanish
References: 40
Page: 7-16
PDF size: 501.74 Kb.


ABSTRACT

Introduction: Clinical simulation activities are often accompanied by pre-delivered supporting instructional material. This, paradoxically, may imply an increase in the demand for mental resources to be able to process them. The mental load theory proposes a limited capacity of the working memory, for which it is necessary to measure the mental load associated with the instructional material.
Objective: To evaluate mental workload in low fidelity simulations in nursing students, with and without the use of interactive instructional material.
Method: Quantitative, experimental, case-control design. The sample was 105 students, of census type, with random assignment to the control and case group. The case group was exposed to video-type instructional material and reading of the learning guide, versus the control group, exposed only to reading. Mental load was measured with the NASA-TXL instrument, after a low-fidelity simulation.
Results: The mean scores for the control and case groups were, respectively: mental demand 5.69 ± 1.93 vs 6.24 ± 2.17 (p›0.05), physical demand 3.22 ± 1.91 vs 3.47 ± 2.13 (p › 0.05), temporal demand 4.89 ± 2.32 vs 5.49 ± 2.71 (p › 0.05), effort 6.98 ± 1.78 vs 7.61 ± 1.83 (p ‹ 0.05), frustration level 4.81 ± 2.50 vs 6.02 ± 2.83 (p ‹ 0.05) and performance 7.91 ± 1.49 vs 7.71 ± 1.45 (p › 0.05).
Conclusions: There were significant differences in the effort and frustration level scales. In the mental, physical and temporal demand scales, the case group presented higher scores, without significant differences. Self-perceived performance was lower in the case group.


REFERENCES

  1. Illesca M, Novoa R, Cabezas M, Hernández A, GonzálezL. Simulación Clínica: opinión de estudiantes de enfermería,Universidad Autónoma de Chile, Temuco. Enfermeria(Montev.). 2019;8(2):51-65. https://doi.org/10.22235/ech.v8i2.1845

  2. Piña-Jiménez I, Amador-Aguilar R. La enseñanza de la enfermeríacon simuladores, consideraciones teórico-pedagógicaspara perfilar un modelo didáctico. Enfer Universitaria.2015;12(3):152-59. https://doi.org/10.1016/j.reu.2015.04.007

  3. Maimon NB, Bez M, Drobot D, Molcho L, Intrator N, KakiashvilliE, Bickel A. Continuous Monitoring of MentalLoad During Virtual Simulator Training for LaparoscopicSurgery Reflects Laparoscopic Dexterity: A ComparativeStudy Using a Novel Wireless Device. Front Neurosci. 2022;15:694010. https://doi.org/10.3389/fnins.2021.694010

  4. Guerra C, Carrasco P, García J. El rol de la simulación en elaprendizaje de habilidades procedimentales en estudiantes deenfermería: historia y desafíos. Rev Med Chile. 2022;150(2):216-21. http://dx.doi.org/10.4067/S0034-98872022000200216

  5. Ayala J, Romero L, Alvarado A, Cuvi G. La simulación clínicacomo estrategia de enseñanza-aprendizaje en cienciasde la salud. Rev Metro Ciencia. 2019;27(1):32-38. Disponibleen: https://revistametrociencia.com.ec/index.php/revista/article/view/60/60

  6. Herrera-Aliaga E, Estrada LD. Trends and Innovations ofSimulation for Twenty First Century Medical Education.Front Public Health. 2022;10:619769. https://doi.org/10.3389/fpubh.2022.619769

  7. Amaya-Afanador A. Catorce pasos para introducir la simulaciónclínica al currículo de medicina y ciencias dela salud. Simulación Clinica. 2019;1(1):55-60. https://doi.org/10.35366/RSC191I

  8. Tremblay ML, Rethans JJ, Dolmans D. Task complexityand cognitive load in simulation-based education: A randomisedtrial. Med Educ. 2023;57(2):161-69. https://doi.org/10.1111/medu.14941

  9. Acevedo E, Díaz J, Cajavilca R, Cobo J. Modelo de diseñoinstruccional aplicado a una guía virtual en simulaciónclínica. Univ Med. 2019;60(3):5-19. https://doi.org/10.11144/javeriana.umed60-3.mdis

  10. Labbé C, López-Neira L, Saiz J, Vinet E, Boero P. Uso deTIC en estudiantes universitarios chilenos: enfoque desdela adultez emergente. PEL. 2019;56(2):1-14. https://doi.org/10.7764/PEL.56.2.2019.2

  11. Lavín S, Zaldívar A, Rodelo J, Zaldívar J. Utilización desmartphone por estudiantes de nivel superior. RITI. 2019;7(14):89-97. https://doi.org/10.36825/RITI.07.14.008

  12. Cortés M, Herrera-Aliaga E. Nomophobia: The smartphoneaddiction. Impact and recommendations for their properuse in healthcare teaching environment. Rev. méd. Chile.2022;150(3):407-408. http://dx.doi.org/10.4067/S0034-98872022000300407.

  13. White G. Mental load: helping clinical learners. ClinTeach. 2011;8(3):168-71. https://doi.org/10.1111/j.1743-498X.2011.00458.x

  14. Díaz-Guio D, Ricardo-Zapata A, Ospina-Velez J, Gómez-Candamil G, Mora-Martinez S, Rodriguez-Morales A. Cognitiveload and performance of health care professionalsin donning and doffing PPE before and after a simulationbasededucational intervention and its implications duringthe COVID-19 pandemic for biosafety. Le Infezioni in Medicina.2020;Suppl.1:111-17.

  15. Rogers BA, Franklin AE. Cognitive load experienced bynurses in simulation-based learning experiences: An integrativereview. Nurse Educ Today. 2021;99:104815. https://doi.org/10.1016/j.nedt.2021.104815

  16. Tokuno J, Carver TE, Fried GM. Measurement and Managementof Cognitive Load in Surgical Education: A NarrativeReview. J Surg Educ. 2023;80(2):208-15. https://doi.org/10.1016/j.jsurg.2022.10.001

  17. Sevcenko N, Ninaus M, Wortha F, Moeller K, Gerjets P. MeasuringCognitive Load Using In-Game Metrics of a SeriousSimulation Game. Front Psychol. 2021 Mar 24;12:572437.https://doi.org/10.3389/fpsyg.2021.572437

  18. Sibbald M, Caners K, Wang B. Managing cognitive load insimulations: exploring the role of simulation technologists.Can Med Educ J. 2019;10(4):e48-e56.

  19. Lapierre A, Arbour C, Maheu-Cadotte MA, RadermakerM, Fontaine G, Lavoie P. Effect of simulation on cognitiveload in health care professionals and students: protocolfor a systematic review and meta-analysis. JBI EvidSynth. 2021 Jun;19(6):1394-403. https://doi.org/10.11124/JBIES-20-00213

  20. Park SH, Goldberg SA, Al-Ballaa A, Tayeb B, Basurrah M,Abahuje E, Miccile C, Pozner CN, Yule S, Dias RD. ObjectiveMeasurement of Learners’ Cognitive Load During Simulation-Based Trauma Team Training: A Pilot Study. J Surg Res.2022;279:361-367. https://doi.org/10.1016/j.jss.2022.06.023

  21. Sweller J. Cognitive load during problem solving: Effectson learning. Cognitive Science. 1988;12:257–85. https://doi.org/10.1207/s15516709cog1202_4

  22. Sweller J. Element interactivity and intrinsic, extraneousand germane cognitive load. Educational Psychology Review.2010;22:123–38. https://doi.org/10.1007/s10648-010-9128-5

  23. Sweller J, Cooper, G. The use of worked examples as a substitutefor problem solving in learning algebra. Cognitionand Instruction. 1985;2,59–89.

  24. Sweller J, Van Merriënboer J, Paas F. Cognitive architectureand instructional design. Educational Psychology Review.1998;10,251–95. https://doi.org/10.1023/a:1022193728205

  25. Meza W, Escobar C. Educacion virtual en imagenologíaaplicada a la terapia: ¿barrera u oportunidad de mejora?Rev Hered Rehab. 2020;2:37-42. https://doi.org/10.20453/rhr.v3i2.4113

  26. Favre-Félix J, Dziadzko M, Bauer C, Duclos A, Lehot JJ,Rimmelé T, Lilot M. High-Fidelity Simulation to AssessTask Load Index and Performance: A Prospective ObservationalStudy. Turk J Anaesthesiol Reanim. 2022;50(4):282-87. https://doi.org/10.5152/TJAR.2022.21234

  27. Díaz-García J, González-Ponce I, Ponce-Bordón JC, López-Gajardo MÁ, Ramírez-Bravo I, Rubio-Morales A, García-Calvo T. Mental Load and Fatigue Assessment Instruments:A Systematic Review. Int J Environ Res Public Health. 2021Dec 31;19(1):419. https://doi.org/10.3390/ijerph19010419

  28. Lowndes BR, Forsyth KL, Blocker RC, Dean PG, Truty MJ,Heller SF, Blackmon S, Hallbeck MS, Nelson H. NASA-TLXAssessment of Surgeon Workload Variation Across Specialties.Ann Surg. 2020;271(4):686-92. https://doi.org/10.1097/SLA.0000000000003058

  29. Díaz E, Rubio S, Martín J, Luceño L. Estudio Psicométrico delÍndice de Carga Mental NASA-TLX con una Muestra de TrabajadoresEspañoles. Rev. psicol. trab. organ. 2010;26(3):191-99. Disponible en: http://scielo.isciii.es/scielo.php?script=sci_arttext&pid=S1576-59622010000300003&lng=es.

  30. Hart SG, Staveland LE. Development of NASA-TLX (TaskLoad Index): Results of empirical and theoretical research.In: Hancock PA, Meshkati N, (eds.) Advances in Psychology.1988;52:139-83. https://doi.org/10.1016/S0166-4115(08)62386-9

  31. Bell SW, Kong JCH, Clark DA, Carne P, Skinner S, PillingerS, Burton P, Brown W. The National Aeronautics and SpaceAdministration-task load index: NASA-TLX: evaluation ofits use in surgery. ANZ J Surg. 2022 Nov;92(11):3022-28.https://doi.org/10.1111/ans.17830

  32. Said S, Gozdzik M, Roche TR, Braun J, Rössler J, KasererA, Spahn DR, Nöthiger CB, Tscholl DW. Validation of theRaw National Aeronautics and Space Administration TaskLoad Index (NASA-TLX) Questionnaire to Assess PerceivedWorkload in Patient Monitoring Tasks: Pooled AnalysisStudy Using Mixed Models. J Med Internet Res. 2020 Sep7;22(9):e19472. https://doi.org/10.2196/19472

  33. Hernandez R, Rol S, Jin H, Schneider S, Pyatak E. Validationof the National Aeronautics and Space Administration TaskLoad Index (NASA-TLX) Adapted for the Whole Day RepeatedMeasures Context. Ergonomics. 2022;65(7):960–75.https://doi.org/10.1080/00140139.2021.2006317

  34. López I, Rubio S, García J, Luceño L. Fase de ponderacióndel NASA-TLX: ¿Un paso necesario en la aplicación delinstrumento? EduPsykhé. Revista de psicología y psicopedagogía.2010;9(2):159-75. Disponible en: https://dialnet.unirioja.es/servlet/articulo?codigo=3437172

  35. López-Núñez I, Rubio-Valdehita S, Díaz-Ramiro E. Cambiosproducidos por la adaptación al EEES en la carga detrabajo de estudiantes de Psicología. REP. 2019;77(272):163-76. https://doi.org/10.22550/REP77-1-2019-02

  36. Olivares V, Jélvez C, Mena L, Lavarello J. Estudios sobreBurnout y Carga Mental en Conductores del Transporte Públicode Chile (Transantiago). Cienc Trab. 2013; 15(48):173-78. http://doi.org/10.4067/S0718-24492013000300011

  37. Lebet RM, Hasbani NR, Sisko MT, Agus MSD, NadkarniVM, Wypij D, Curley MAQ. Nurses’ Perceptions of WorkloadBurden in Pediatric Critical Care. Am J Crit Care.2021;30(1):27-35. https://doi.org/10.4037/ajcc2021725

  38. Josephsen J. Cognitive load measurement, Worked-outmodeling, and simulation. Clinical Simulation in Nursing.2018;23:10-5. https://doi.org/10.1016/j.ecns.2018.07.004

  39. Farías M, Obilinovic K, Orrego R. El principio y efecto deredundancia en la retención y transferencia de expresionesidiomáticas en inglés como lengua extranjera. Íkala, revistade lenguaje y cultura. 2013;18(1):9-17. Disponible en: https://www.redalyc.org/articulo.oa?id=255026360007

  40. Ruiz-Rabelo J, Navarro-Rodriguez E, Di-Stasi L, Díaz-JiménezN, Cabrera-Bermon J, Díaz-Iglesias C, Gomez-AlvarezM, Briceño-Delgado J. Validation of the NASA-TLX Scorein Ongoing Assessment of Mental Workload During a LaparoscopicLearning Curve in Bariatric Surgery. Obes Surg.2015;25(12):2451-56. https://doi.org/10.1007/s11695-015-1922-1




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